Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
404 detections
Filters
Last updated
All Time
Detection languages
193
104
95
4
3
Contributors
90
77
62
50
22
Categories
231
151
101
83
77
Platforms
270
109
39
18
9
Products / Services
10,665
9,758
6,692
4,421
3,749
404
MITRE Techniques
138
119
74
64
47
CVEs
4
2
2
2
1
IDS Classtypes
1
IDS Protocols
1
Detects outbound HTTP/HTTPS POST requests where the URI, query string, or path contains evidence of sensitive credential material, such as AWS access keys, private key blocks, or common environment variable patterns, indicative of potential credential harvesting and exfiltration to an external destination.
Detects unauthorized outbound network traffic from browser processes to the lookalike domain 'pdf.gusercontent.com'. This domain is associated with a malicious Firefox browser extension, 'PDF Identity Verifier', which is designed to exfiltrate session telemetry and data from Google account sessions.
Detects web proxy requests that resemble phishing attempts targeting Apple Activation Lock. The rule identifies URLs containing specific Apple-related keywords in combination with common phishing URL paths, while filtering out legitimate Apple support documentation pages.
Detects network activity associated with the GhostCode phishing kit backend. The rule monitors for specific API endpoints used for credential and MFA harvesting, including loading configurations, geolocation, and polling for captured data, combined with specific session cookie identifiers.
Detects HTTP POST requests to a known suspicious endpoint ('/board.php') often used by the Chinotto Python backdoor. The rule monitors for outgoing web traffic containing 'data=' parameters or connections to known malicious domains, indicating potential exfiltration of base64-encoded command output.
Detects potential AI-targeted cloaking, a technique where a web server serves different content to AI crawlers versus human users, identified by comparing HTTP response sizes or hashes across session logs. The rule uses Microsoft Sentinel's ASIM Web Session schema to correlate web requests, identifying discrepancies that suggest malicious or evasive intent. Covers T1036 & T1027
Detects potential AI-targeted cloaking, a technique where a web server serves different content to AI crawlers versus human users, identified by comparing HTTP response sizes or hashes across session logs. The rule uses Microsoft Sentinel's ASIM Web Session schema to correlate web requests, identifying discrepancies that suggest malicious or evasive intent. Covers T1036 & T1027
This rule detects indicators of Browser-in-the-Browser (BitB) phishing attacks within web proxy traffic. It monitors for suspicious HTML markup mimicking browser UI elements, such as fake title bars and URL bars, as well as specific window dimensions and authentication lures that deviate from known legitimate identity provider patterns.
Detects network requests originating from mobile device user-agents to suspected phishing or OAuth-consent URLs. This rule identifies patterns common in 'quishing' (QR-code phishing) campaigns where a mobile device is used to interact with a malicious redirect chain or credential-harvesting page. It excludes known legitimate OAuth authorization flows to reduce noise.
This rule establishes a daily baseline of request volumes to mail.google.com per user and per host using proxy logs. It identifies anomalous spikes in traffic or unexpected users/hosts accessing personal webmail, which may indicate data exfiltration using a legitimate web service.
Detects outbound network requests to OpenAI Assistants API endpoints (threads, assistants, runs) that do not originate from common web browsers. This activity may indicate malicious usage of AI services, such as command and control communication via AI agents or automated exfiltration scripts, as opposed to legitimate user-initiated browsing.
Detects proxy requests directed towards the Microsoft OAuth2 device authorization endpoint originating from suspicious referrers (e.g., .de top-level domains). This pattern is consistent with device code phishing attacks where users are redirected from external malicious sites to a legitimate Microsoft authentication page to obtain an authorization code.
Detects web proxy requests that resemble phishing attempts targeting Apple Activation Lock. The rule identifies URLs containing specific Apple-related keywords in combination with common phishing URL paths, while filtering out legitimate Apple support documentation pages.
Detects potential AI-targeted cloaking, a technique where a web server serves different content to AI crawlers versus human users, identified by comparing HTTP response sizes or hashes across session logs. The rule uses Microsoft Sentinel's ASIM Web Session schema to correlate web requests, identifying discrepancies that suggest malicious or evasive intent. Covers T1036 & T1027
Detects web traffic directed towards the AnonyMousKIT SMS relay API endpoint, commonly used by threat actors for dispatching SMS phishing lures. The rule monitors for requests to specific API paths related to SMS dispatching and analyzes the gateway status messages returned by the service.
Detects an adversary-in-the-middle (AiTM) phishing pattern where the legitimate Microsoft authentication URL is embedded as a sub-path within an attacker-controlled proxy domain. This technique is characteristic of AiTM kits, such as Evilginx2, which proxy the legitimate Microsoft authentication flow to capture credentials and session cookies.
Detects outbound web requests to the Telegram API triggered by Google Apps Script components (sidebar macros). This pattern is indicative of malicious Google Docs or Slides files using embedded scripts to exfiltrate data or perform command-and-control communication via the Telegram API when the document is opened by a user.
Detects outbound proxy traffic indicating potential Adversary-in-the-Middle (AiTM) phishing activity. The rule identifies requests directed at domains mimicking major Identity Providers (Microsoft, Okta, Duo, Google) that either utilize punycode homograph encoding or arrive via known URL shortener/redirector services, while filtering out known legitimate brand domains.
Detects outbound network requests from endpoints to known 'uncensored' or jailbroken LLM-as-a-Service domains (e.g., WormGPT, FraudGPT). These platforms are specifically marketed to threat actors for illicit purposes like generating malware, phishing kits, or exploit code, and identifying access to them serves as a leading indicator of adversarial activity.
Detects outbound network requests from endpoints to known 'uncensored' or jailbroken LLM-as-a-Service domains (e.g., WormGPT, FraudGPT). These platforms are specifically marketed to threat actors for illicit purposes like generating malware, phishing kits, or exploit code, and identifying access to them serves as a leading indicator of adversarial activity.
Detects HTTP(S) requests to known SideCopy/ReverseRAT payload-delivery URLs identified in Operation SideCopy spear-phishing campaigns targeting Indian academia.
Page 2 of 20